rag-mcp

A RAG service based on FastMCP that enables document indexing and retrieval (keyword/vector search) through the MCP protocol.

→ Ma-fee/RAG_MCP · listed on glama

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// key findings

✅

No credential exfiltration, no sensitive file access, no obfuscation

Static analysis found nothing flowing your secrets to unexpected places.

🔐

You'll be asked for 2 credentials: EMBEDDING_API_KEY, MULTIMODAL_API_KEY

These are read from process.env at runtime. Make sure you trust where they’ll be sent.

// required environment variables

This server reads these from process.env. You'll be asked to provide them before it can run.

configRAG_MCP_DATA_DIR— .rag_mcp_data 索引数据目录

configHTTP_HOST— 127.0.0.1 SSE 模式监听地址（sse 模式有效）

configHTTP_PORT— 8787 SSE 模式监听端口（sse 模式有效）

🔐 secretEMBEDDING_API_KEY— 编辑 .env，至少填入（vector 搜索必需）

configEMBEDDING_DIMENSION— 自动检测向量维度（可选）

configEMBEDDING_TIMEOUT_SECONDS— 30 请求超时秒数

configDEFAULT_TOP_K— 5 默认返回结果数

configKEYWORD_TOP_K— 8 关键词检索候选数

configCHUNK_SIZE— 800 分块大小（字符数）

configCHUNK_OVERLAP— 120 分块重叠（字符数）

🔐 secretMULTIMODAL_API_KEY

configMULTIMODAL_BASE_URL

configMULTIMODAL_MODEL

configMCP_TRANSPORT— stdio 传输模式：stdio 或 sse

// full audit trail

The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.

// improvement guidance — verified publishers only

We have 6 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.

// embed badge in your README

[![M8ven Score](https://m8ven.ai/badge/mcp/ma-fee-rag-mcp-rdk7iq)](https://m8ven.ai/mcp/ma-fee-rag-mcp-rdk7iq)

commit: 7c17cb3e70bb55b2ffcada4afcc545da26b52b02

code hash: e5292605cc8f6921579e530a4b00f87156a5230e0ed7cf3d03485c7e5fe22dd2

verified: 6/21/2026, 10:32:05 AM

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